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We investigate the use of modularity as a quantifier of whole-brainfunctional networks. Brain networks are constructed from functional magneticresonance imaging while subjects listened to auditory pieces that varied inemotivity and cultural familiarity. The results of our analysis reveal high andlow modularity groups based on the network configuration during a subject'sfavorite song, and this classification can predict network reconfigurationduring the other auditory pieces. In particular, subjects in the low modularitygroup show significant brain network reconfiguration during both familiar andunfamiliar pieces. In contrast, the high modularity brain networks appear morerobust and only exhibit significant changes during the unfamiliar music andspeech. We also find differences in the stability of module composition for thetwo groups during each auditory piece. Our results suggest that the modularityof the whole-brain network plays a significant role in the way the networkreconfigures during varying auditory processing demands, and it may thereforecontribute to individual differences in neuroplasticity capability duringtherapeutic music engagement.

Modularity allows classification of human brain networks during music and speech perception